Numerical prediction of component-ratio-dependent compressive strength of bone cement

• Autorzy: Machrowska Anna , Karpiński Robert , Jonak Józef , Szabelski Jakub , Krakowski Przemysław
• Języki publikacji: EN

Abstrakty

EN

Changes in the compression strength of the PMMA bone cement with a variable powder/liquid component mix ratio were investigated. The strength test data served to develop basic mathematical models and an artificial neural network was employed for strength predictions. The empirical and numerical results were compared to determine modelling errors and assess the effectiveness of the proposed methods and models. The advantages and disadvantages of mathematical modelling are discussed.

Słowa kluczowe

EN

artificial neural networks; mathematical modelling; biomaterials; bone cement

PL

sztuczne sieci neuronowe; modelowanie matematyczne; biomateriały; cement kostny

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2020
• Tom: Vol. 16, no 3
• Strony: 87--101
• Opis fizyczny: Bibliogr. 30 poz., fig.

Twórcy

autor

Machrowska Anna

• Lublin University of Technology Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Nadbystrzycka 36, 20-618 Lublin, Poland

autor

Karpiński Robert

• Lublin University of Technology Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Nadbystrzycka 36, 20-618 Lublin, Poland

autor

Jonak Józef

• Lublin University of Technology Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Nadbystrzycka 36, 20-618 Lublin, Poland

autor

Szabelski Jakub

• Lublin University of Technology, Faculty of Mechanical Engineering Department of Computerization and Production Robotization, Section of Biomedical Engineering, Nadbystrzycka 36, 20-618 Lublin, Poland

autor

Krakowski Przemysław

• Medical University of Lublin Department of Trauma Surgery and Emergency Medicine, Staszica 16, 20-081 Lublin, Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).